Landscapes, conservation and global change.

My research addresses broadly the structure and dynamics of ecological systems. The major question of my research program is how can we use modeling to scale-up microecological mechanisms related to individual traits and physical processes to predict macroecological outcomes such as population persistence, community organization, ecosystem function, biogeographic patterns and climate change impacts. Some of the tools I use include individual-based modeling, wavelet-based time series analysis and hierarchical Bayesian estimation. I collaborate broadly with empirical and experimental scientists and the majority of my students pursue field studies. We have worked in a variety of environments including Madagascar, Brazil, Southern Africa, Fiji, Micronesia, China, Taiwan, Baja California, Veracruz and Texas.

Recent Publications

Island systems have long played a central role in the development of ecology and evolutionary biology. However, while many empirical studies suggest species differ in vital biogeographic rates, such as dispersal abilities, quantitative methods have had difficulty incorporating such differences into analyses of whole-assemblages. In particular, differences in dispersal abilities among species can cause variation in the spatial clustering and localization of species distributions. Here, we develop a single, hierarchical Bayes, assemblage-wide model of 252 bird species distributions on the islands of Northern Melanesia and use it to investigate a) whether dispersal limitation structures bird assemblages across the archipelago, b) whether species differ in dispersal ability, and c) test the hypothesis that wing aspect ratio, a trait linked to flight efficiency, predicts differences inferred by the model. Consistent with island biogeographic theory, we found that individual species were more likely to occur on islands with greater area, and on islands near to other islands where the species also occurred. However, species showed wide variation in the importance and spatial scale of these clustering effects. The importance of clustering in distributions was greater for species with low wing aspect ratios, and the spatial scale of clustering was also smaller for low aspect ratio species. These findings suggest that the spatial configuration of islands interacts with species dispersal ability to affect contemporary distributions, and that these species differences are detectable in occurrence patterns. More generally, our study demonstrates a quantitative, hierarchical approach that can be used to model the influence of dispersal heterogeneity in diverse assemblages and test hypotheses for how traits drive dispersal differences, providing a framework for deconstructing ecological assemblages and their drivers.This article is protected by copyright. All rights reserved.

Ecological forecasting requires information about the climatic conditions experienced by organisms. Despite impressive methodological and computational advances, ecological forecasting still suffers from poor resolutions of environmental data. Published data comprise relatively few layers of surface climate and suffer from coarse temporal resolution. Hence, models using these data might underestimate heterogeneity of microclimates and miss biological consequences of climatic extremes. Moreover, we currently lack predictions about vegetation cover in future environments, a key factor for estimating the spatial heterogeneity of microclimates and hence the capacity for behavioral thermoregulation. Here, we describe microclimates and vegetation for the past and the future at spatial and temporal resolutions of 36 km (approximately 0.3°) and 1 h, respectively. We used the Weather Research and Forecasting model to downscale published, bias-corrected predictions of a global-circulation model from a resolution of 0.9° latitude and 1.25° (approximately 100 km in latitude and 130 km in longitude). Output from this model was used as input for a microclimate model, which generated temperatures and wind speeds for 1980–1999 and 2080–2099 at various heights, as well as soil temperatures at various depths and shade intensities. We also predicted the percentage of green vegetation and the percentage of shade given the angle of the sun. These data were evaluated using several criteria, each of which shed light on a different aspect of value to researchers. The metadata describe the modeling protocol, microclimate calculations, computer programs, and the evaluation process.This article is protected by copyright. All rights reserved.

As global warming has lengthened the active seasons of many species, we need a framework for predicting how advances in phenology shape the life history and the resulting fitness of organisms. Using an individual-based model, we show how warming differently affects annual cycles of development, growth, reproduction and activity in a group of North American lizards. Populations in cold regions can grow and reproduce more when warming lengthens their active season. However, future warming of currently warm regions advances the reproductive season but reduces the survival of embryos and juveniles. Hence, stressful temperatures during summer can offset predicted gains from extended growth seasons and select for lizards that reproduce after the warm summer months. Understanding these cascading effects of climate change may be crucial to predict shifts in the life history and demography of species.

Microbial responses to climate change will partly control the balance of soil carbon storage and loss under future temperature and precipitation conditions. We propose four classes of response mechanisms that can allow for a more general understanding of microbial climate responses. We further explore how a subset of these mechanisms results in microbial responses to climate change using simulation modeling. Specifically, we incorporate soil moisture sensitivity into two current enzyme-driven models of soil carbon cycling and find that moisture has large effects on predictions for soil carbon and microbial pools. Empirical efforts to distinguish among response mechanisms will facilitate our ability to further develop models with improved accuracy.

Recent models predict contrasting impacts of climate change on tropical and temperate species, but these models ignore how environmental stress and organismal tolerance change during the life cycle. For example, geographical ranges and extinction risks have been inferred from thermal constraints on activity during the adult stage. Yet, most animals pass through a sessile embryonic stage before reaching adulthood, making them more susceptible to warming climates than current models would suggest. By projecting microclimates at high spatio-temporal resolution and measuring thermal tolerances of embryos, we developed a life cycle model of population dynamics for North American lizards. Our analyses show that previous models dramatically underestimate the demographic impacts of climate change. A predicted loss of fitness in 2% of the USA by 2100 became 35% when considering embryonic performance in response to hourly fluctuations in soil temperature. Most lethal events would have been overlooked if we had ignored thermal stress during embryonic development or had averaged temperatures over time. Therefore, accurate forecasts require detailed knowledge of environmental conditions and thermal tolerances throughout the life cycle.